Research And Application Of Multi-Time Scale Optimal Scheduling For Highway Isolated Microgrid

With the development of Chinese highway network construction,the energy demand of highway construction is rising rapidly,and it is urgent to build a safe,economic and green energy transportation.To ensure the secure and steady operations of highway electricity supply systems in weak or gridless regions,it is of great moral and practical significance to study the optimal dispatching of isolated highway microgrid systems that can simultaneously enhance the operation efficiency of electricity supply systems and decrease carbon emissions.To analyze the effects of the double perturbation caused by the scenery power output uncertainty and the load demand randomness on the highway islanded microgrid operation,this paper builds the power output model of PV and wind turbine and the electricity supply model of the energy storage system and the diesel generation system based on the fundamental architecture of the highway islanded microgrid system;from the four dimensions of grid entry moment,charge state,charging and discharging time and output power,the Monte Carlo method is applied to analyze the charging and discharging characteristics of highway EVs on the highway network,and the EV charging load model is established to lay the theoretical basis for the subsequent research on the optimal scheduling of highway islanding microgrid.Considering the random and intermittent nature of the renewable energy output and the impact of the disorderly grid connection of EVs on the safe and stable operation of the dispatchable units in the isolated highway microgrid,this paper designs a multi-time scale optimal dispatching strategy for the isolated highway microgrid considering the economic compensation to guide the participation of EVs in the optimal dispatching of the microgrid,which is carried out in a multi-level coordination and level-by-level refinement manner in two stages: day-ahead and intra-day.Optimization.In particular,the day-ahead scheduling aims at maximizing microgrid operation revenue and minimizing carbon emission,and uses multiobjective quantum genetic algorithm to optimize the capacity of dispatchable units in the system considering system power balance,electric load reserve capacity and microgrid operation equipment working constraints to obtain the day-ahead scheduling plan;the intra-day scheduling aims at minimizing the adjustment of the day-ahead scheduling plan,and uses model prediction control to revise the intra-day equipment The intra-day scheduling is aimed at minimizing the adjustment of the intra-day scheduling plan,and the model prediction control is used to correct the intra-day equipment output.Taking a highway microgrid as an example,considering the natural conditions and load levels on typical travel days and peak travel periods,the economic benefits and carbon emissions of the operation of the highway island microgrid are compared and analyzed before and after the participation of electric vehicles in the scheduling,and the effectiveness and rationality of the multi-time scale optimal scheduling strategy of the highway island microgrid are verified under different load levels on typical travel days and peak travel periods.The effectiveness and rationality of the multi-timescale optimal scheduling strategy for highway islanded microgrids are verified under different load levels on typical travel days and peak travel periods.The research results of this thesis enriched the theoretical method system of highway islanded microgrid optimization and dispatching,broadened the application scope of Monte Carlo method,multi-objective quantum genetic algorithm and model predictive control in the highway field,and provided solutions and useful references for highway microgrid operation and operation,with certain theoretical research and practical guidance significance.